DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first
inventor to file provisions of the AIA .
Status of Claims
This is the first Office action on the merits. Claims 1-15 are currently pending and addressed below.
Claim Objections
Claim 13 is objected to because of the following informalities:
Claim 13 recites “A non-transitory computer-readable medium comprising instructions including…”
Claim 13 should read “A non-transitory computer-readable medium comprising instructions which, when executed by a processor, cause the processor to execute operations including:…”. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mental process without significantly more.
101 Analysis – Step 1
Claims 1 and 13-14 are directed to a computer-implemented method (i.e., a process), non-transitory computer-readable medium (i.e., a machine), and apparatus (i.e., a machine). Therefore, claims 1 and 13-14 are within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claims 1 and 13-14 include limitations that recite an abstract idea and will be used as a representative claim for the remainder of the 101 rejection.
Independent claims 1 and 13-14 recite the following information:
A computer-implemented method/non-transitory computer-readable medium comprising instructions/apparatus for estimating a road layout according to a driving direction of a vehicle in a vehicle assistance system comprising:
a processor configured to execute the instructions, wherein the instructions include:
receiving a sensor signal, wherein:
a first part of the sensor signal deviates from the road layout, and
a second part of the sensor signal corresponds to the road layout indicated by a shape of a road guard rail;
removing one or more irregularities from the first part of the sensor signal with respect to the driving direction of the vehicle to obtain a modified sensor signal; and
obtaining the estimated road layout according to the modified sensor signal.
The examiner submits that the foregoing bolded limitation(s) constitute an abstract idea of a mental process that gathers information on obtained sensor signals with respect to the driving direction of a vehicle, analyzes the obtained information to identify anomalies in the data or error, and removes the anomalous data to obtain modified sensor data that eliminates errors from the data.
Each of the limitations can be performed in the mental realm or by using pen and paper to gather information based on visual observation of displayed sensor data obtained while a vehicle is driven, evaluate the gathered information to identify noise or errors within the data, and adjust the gathered data by removing erroneous data caused by possible noise in order to work with more accurate and reliable sensor data.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
Claims 1 and 13-14 do contain additional elements of a non-transitory computer-readable medium comprising instructions, apparatus for estimating a road layout according to a driving direction of a vehicle in a vehicle assistance system, a processor configured to execute the instructions, receiving a sensor signal, wherein: a first part of the sensor signal deviates from the road layout, and a second part of the sensor signal corresponds to the road layout indicated by a shape of a road guard rail, and obtaining the estimated road layout according to the modified sensor signal. However, these additional elements do not add to significantly more than the abstract idea of a mental process.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional elements of a non-transitory computer-readable medium comprising instructions, apparatus for estimating a road layout according to a driving direction of a vehicle in a vehicle assistance system, a processor configured to execute the instructions, receiving a sensor signal, wherein: a first part of the sensor signal deviates from the road layout, and a second part of the sensor signal corresponds to the road layout indicated by a shape of a road guard rail, and obtaining the estimated road layout according to the modified sensor signal, the examiner submits that these limitations merely describe how to generally apply the otherwise mental judgements in a generic or general-purpose vehicle navigation assistance system environment. The non-transitory computer-readable medium comprising instructions, apparatus for estimating a road layout according to a driving direction of a vehicle in a vehicle assistance system, a processor configured to execute the instructions, receiving a sensor signal, wherein: a first part of the sensor signal deviates from the road layout, and a second part of the sensor signal corresponds to the road layout indicated by a shape of a road guard rail, and obtaining the estimated road layout according to the modified sensor signal are recited at a high level of generality and merely automate the sensor signal receiving, data analyzing and removing to obtain modified data, and road layout estimating components of the system. As for the additional elements specifying receiving a sensor signal, wherein: a first part of the sensor signal deviates from the road layout, and a second part of the sensor signal corresponds to the road layout indicated by a shape of a road guard rail, and obtaining the estimated road layout according to the modified sensor signal, the examiner submits that these limitations are recited at a high level of generality (i.e., describe general means of the signal receiving, removing irregularities from the sensor signal to obtain a modified sensor signal, and road layout according to the modified sensor signal estimating steps) and therefore amount to mere transmission of data between computer processing components and presenting of an estimated road layout as an output which is a form of insignificant extra-solution activity that merely uses computing components to perform the process.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B, representative independent claims 1 and 13-14 do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a non-transitory computer-readable medium comprising instructions, apparatus for estimating a road layout according to a driving direction of a vehicle in a vehicle assistance system, a processor configured to execute the instructions, receiving a sensor signal, wherein: a first part of the sensor signal deviates from the road layout, and a second part of the sensor signal corresponds to the road layout indicated by a shape of a road guard rail, and obtaining the estimated road layout according to the modified sensor signal amount to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of gathering/transmitting and presenting data, the examiner submits that these limitations are insignificant extra-solution activities.
Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The additional limitations of gathering/transmitting data are well-understood, routine, and conventional activities because the specification does not provide any indication that the computer is anything other than a conventional computer. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner. Hence, the claims are not patent eligible.
Dependent claims 2-12 (method claims) and 15 (apparatus claims) do not recite and further limitations that cause the claims to be patent eligible. The limitations of the dependent claims are directed towards additional aspects of the judicial exception that do not integrate the judicial exception into a practical application. The dependent claims further narrow the scope of independent claims 1 and 13-14, however, the identified additional limitations and elements still do not impose any meaningful limits on practicing the identified abstract ideas. Therefore, dependent claims 2-12 and 15 are not patent eligible under the same rationale as provided for in the rejection of claims 1 and 13-14. Therefore, claims 1-15 are ineligible under 35 USC §101.
Examiner notes that amending claims 1 and 13-14 to necessarily include physical actuation to control movement of a vehicle would render the claimed invention eligible.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-4 and 11-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Silver et al. US 9395192 B1 (“Silver”).
For claim 1, Silver discloses a computer-implemented method for estimating a road layout according to a driving direction of a vehicle in a vehicle assistance system (See at least Col. 3 lines 39-52 – “… the vehicle's computing system may use data provided by sensors and/or other sources to detect and locate nearby boundaries associated with the road that the vehicle is navigating…may detect lane markers, road curbs, guard rails, or other types of boundaries in the local environment of the vehicle…” and Fig. 5 of Silver – vehicle 500 detecting a guard rail ahead of the vehicle), the method comprising:
receiving a sensor signal (See at least Col. 13 lines 10-17 of Silver – “… A vehicle … may be equipped with various sensors, which all may be configured to capture data representative of the vehicle's environment. For example, the vehicle may include LIDAR, RADAR, a stereo camera system, and/or other types of sensors configured to obtain environment data…”), wherein:
a first part of the sensor signal deviates from the road layout (See at least Col. 18 lines 31-46 of Silver – “…The computing system may remove boundaries within the data in the case that the computing system determined the boundary may have resulted from data-acquisition noise… include a connected structure that does not suddenly change orientation or position in a manner unlike most boundaries… may also fill in portions of boundaries that may have been undetected due to obstacles in the way, such as parked vehicles or road signs…”), and
a second part of the sensor signal corresponds to the road layout indicated by a shape of a road guard rail (See at least Col. 20 lines 51-67 through Col. 21 lines 1-8 – “… the computing system of a vehicle may execute processes relating to a smoothness check upon the boundary data and/or edge data… may use threshold determinations to filter boundary data to reflect boundaries that may actually exist in the vehicle's local environment… a guard rail positioned on the side of a road, such as a highway, may not likely include segments of sharp changes in orientation and position…” and Fig. 5 of Silver – vehicle 500 detecting a guard rail ahead of the vehicle);
removing one or more irregularities from the first part of the sensor signal with respect to the driving direction of the vehicle to obtain a modified sensor signal (See at least Col. 18 lines 31-46 of Silver – “…The computing system may remove boundaries within the data in the case that the computing system determined the boundary may have resulted from data-acquisition noise… may also fill in portions of boundaries that may have been undetected due to obstacles in the way, such as parked vehicles or road signs…”); and
obtaining the estimated road layout according to the modified sensor signal (See at least Col. 18 lines 31-46 of Silver – “… the computing system may adjust the boundary data to remove boundaries… within the data in the case that the computing system determined the boundary may have resulted from data-acquisition noise… may also fill in portions of boundaries that may have been undetected due to obstacles in the way… may adjust the boundary data to reflect any data acquired about the local environment of the vehicle that may indicate the boundary data may need adjustments…”).
For claim 2, Silver discloses wherein:
the first part of the sensor signal includes a first plurality of data points (See at least Col. 18 lines 31-46 of Silver – “…The computing system may remove boundaries within the data in the case that the computing system determined the boundary may have resulted from data-acquisition noise…”); and
removing one or more irregularities from the first part of the sensor signal includes reducing a deviation between at least one data point of the first plurality of data points and the road layout according to the driving direction (See at least Col. 18 lines 31-46 of Silver – “… the computing system may adjust the boundary data to remove boundaries… within the data in the case that the computing system determined the boundary may have resulted from data-acquisition noise… may also fill in portions of boundaries that may have been undetected due to obstacles in the way… may adjust the boundary data to reflect any data acquired about the local environment of the vehicle that may indicate the boundary data may need adjustments…”).
For claim 3, Silver discloses wherein:
reducing the deviation includes:
non-linearly filtering the first plurality of data points (See at least Col. 16 lines 7-16 of Silver – “…the computing system may also use Canny edge detection to apply a filter based on a Gaussian (e.g., bell curve) to filter noise…”); and
obtaining a plurality of non-linearly filtered data points (See at least Col. 16 lines 7-16 of Silver – “…the computing system may also use Canny edge detection to apply a filter based on a Gaussian (e.g., bell curve) to filter noise. The computing system may be configured to store the edge data in memory…”); and
obtaining the estimated road layout according to the modified sensor signal is based on the plurality of non-linearly filtered data points (See at least Col. 16 lines 7-20 of Silver – “…the computing system may also use Canny edge detection to apply a filter based on a Gaussian (e.g., bell curve) to filter noise. The computing system may be configured to store the edge data in memory… an example implementation of using Canny edge detection, a computing system of the vehicle may identify locations as represented by a data-grid that may likely correspond to a boundary over other locations…”).
For claim 4, Silver discloses wherein non-linearly filtering includes:
applying a non-linear low pass filter on the first plurality of data points (See at least Col. 16 lines 7-16 of Silver – “…the computing system may also use Canny edge detection to apply a filter based on a Gaussian (e.g., bell curve) to filter noise…”).
For claim 11, Silver discloses wherein:
the method further includes determining one or more properties of the sensor signal (See at least Col. 4 lines 14-17 of Silver – “…the computing system may modify edge data to fill in edges within small gaps in structure that may have resulted from noise or other system defects, for example. In some instances, gaps may occur due to occlusions, which may result from interference by other vehicles …”);
the one or more properties are one or more of: a distribution of data points within the sensor signal (See at least Col. 4 lines 14-17 of Silver – “…the computing system may modify edge data to fill in edges within small gaps in structure that may have resulted from noise or other system defects, for example. In some instances, gaps may occur due to occlusions, which may result from interference by other vehicles …”), an initial amount of data points within the sensor signal, or a predefined amount of required data points within the sensor signal; and
the method further includes increasing an amount of data points of at least the first plurality of data points using up sampling according to the one or more determined properties of the sensor signal (See at least Col. 4 lines 14-17 of Silver – “…the computing system may modify edge data to fill in edges within small gaps in structure that may have resulted from noise or other system defects… gaps may occur due to occlusions, which may result from interference by other vehicles …”).
For claim 12, Silver discloses wherein:
the method further includes determining an operating instruction based on the estimated road layout affecting a function of the vehicle assistance system (See at least Col. 3 lines 39-52 of Silver – “… the vehicle's computing system may use data provided by sensors and/or other sources to detect and locate nearby boundaries associated with the road that the vehicle is navigating… computing system may use the detected boundaries to … assist in other aspects of navigation… to detect when to execute a turn or to find a different road...”); and
the function includes at least one of:
triggering a steering command for the vehicle (See at least Col. 3 lines 39-52 of Silver – “… the vehicle's computing system may use data provided by sensors and/or other sources to detect and locate nearby boundaries associated with the road that the vehicle is navigating… to detect when to execute a turn...”),
conducting a vehicle path planning, or
triggering a warning for a driver of the vehicle.
For claim 13, Silver discloses a non-transitory computer-readable medium comprising instructions (See at least Col. 10 lines 47-54 of Silver – “…memory 114… may comprise… one or more non-volatile storage components… contain the instructions 115 … executable by the processor 113 to execute … the functions or methods described herein…”) including:
receiving a sensor signal (See at least Col. 13 lines 10-17 of Silver – “… A vehicle … may be equipped with various sensors, which all may be configured to capture data representative of the vehicle's environment. For example, the vehicle may include LIDAR, RADAR, a stereo camera system, and/or other types of sensors configured to obtain environment data…”), wherein:
a first part of the sensor signal deviates from a road layout (See at least Col. 18 lines 31-46 of Silver – “…The computing system may remove boundaries within the data in the case that the computing system determined the boundary may have resulted from data-acquisition noise… include a connected structure that does not suddenly change orientation or position in a manner unlike most boundaries… may also fill in portions of boundaries that may have been undetected due to obstacles in the way, such as parked vehicles or road signs…”), and
a second part of the sensor signal corresponds to the road layout indicated by a shape of a road guard rail (See at least Col. 20 lines 51-67 through Col. 21 lines 1-8 – “… the computing system of a vehicle may execute processes relating to a smoothness check upon the boundary data and/or edge data… may use threshold determinations to filter boundary data to reflect boundaries that may actually exist in the vehicle's local environment… a guard rail positioned on the side of a road, such as a highway, may not likely include segments of sharp changes in orientation and position…” and Fig. 5 of Silver – vehicle 500 detecting a guard rail ahead of the vehicle);
removing one or more irregularities from the first part of the sensor signal with respect to a driving direction of a vehicle to obtain a modified sensor signal (See at least Col. 18 lines 31-46 of Silver – “…The computing system may remove boundaries within the data in the case that the computing system determined the boundary may have resulted from data-acquisition noise… may also fill in portions of boundaries that may have been undetected due to obstacles in the way, such as parked vehicles or road signs…”); and
obtaining an estimated road layout according to the modified sensor signal (See at least Col. 18 lines 31-46 of Silver – “… the computing system may adjust the boundary data to remove boundaries… within the data in the case that the computing system determined the boundary may have resulted from data-acquisition noise… may also fill in portions of boundaries that may have been undetected due to obstacles in the way… may adjust the boundary data to reflect any data acquired about the local environment of the vehicle that may indicate the boundary data may need adjustments…”).
For claim 14, Silver discloses an apparatus (See at least the Abstract of Silver – “… a computing system of a vehicle may receive boundary data associated with a road and may determine edge data representative of edges of the boundaries…”) comprising:
a memory medium configured to store instructions (See at least Col. 10 lines 47-54 of Silver – “…memory 114… may comprise… one or more non-volatile storage components… contain the instructions 115 … executable by the processor 113 to execute … the functions or methods described herein…”); and
a processor configured to execute the instructions (See at least Col. 10 lines 47-54 of Silver – “…memory 114… contain the instructions 115 … executable by the processor 113 to execute … the functions or methods described herein…”), wherein the instructions include:
receiving a sensor signal (See at least Col. 13 lines 10-17 of Silver – “… A vehicle … may be equipped with various sensors, which all may be configured to capture data representative of the vehicle's environment. For example, the vehicle may include LIDAR, RADAR, a stereo camera system, and/or other types of sensors configured to obtain environment data…”), wherein:
a first part of the sensor signal deviates from a road layout (See at least Col. 18 lines 31-46 of Silver – “…The computing system may remove boundaries within the data in the case that the computing system determined the boundary may have resulted from data-acquisition noise… include a connected structure that does not suddenly change orientation or position in a manner unlike most boundaries… may also fill in portions of boundaries that may have been undetected due to obstacles in the way, such as parked vehicles or road signs…”), and
a second part of the sensor signal corresponds to the road layout indicated by a shape of a road guard rail (See at least Col. 20 lines 51-67 through Col. 21 lines 1-8 – “… the computing system of a vehicle may execute processes relating to a smoothness check upon the boundary data and/or edge data… may use threshold determinations to filter boundary data to reflect boundaries that may actually exist in the vehicle's local environment… a guard rail positioned on the side of a road, such as a highway, may not likely include segments of sharp changes in orientation and position…” and Fig. 5 of Silver – vehicle 500 detecting a guard rail ahead of the vehicle);
removing one or more irregularities from the first part of the sensor signal with respect to a driving direction of a vehicle to obtain a modified sensor signal (See at least Col. 18 lines 31-46 of Silver – “…The computing system may remove boundaries within the data in the case that the computing system determined the boundary may have resulted from data-acquisition noise… may also fill in portions of boundaries that may have been undetected due to obstacles in the way, such as parked vehicles or road signs…”); and
obtaining an estimated road layout according to the modified sensor signal (See at least Col. 18 lines 31-46 of Silver – “… the computing system may adjust the boundary data to remove boundaries… within the data in the case that the computing system determined the boundary may have resulted from data-acquisition noise… may also fill in portions of boundaries that may have been undetected due to obstacles in the way… may adjust the boundary data to reflect any data acquired about the local environment of the vehicle that may indicate the boundary data may need adjustments…”).
For claim 15, Silver discloses a vehicle comprising:
the apparatus of claim 14 (See at least Fig. 1 of Silver – automobile 100 with the sensor system and processor to execute the functions provided in Silver).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 5 and 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Silver in view of Hansson EP 3798665 A1 (“Hansson”).
For claim 5, Silver discloses wherein:
the method further includes down sampling the plurality of non-linearly filtered data points and a plurality of data points of the second part of sensor signal to obtain a second plurality of data points (See at least Col. 17 lines 18-30 of Silver – “… one example implementing involving executing modification upon a set or subset of edge data… the modifications executed by the computing system may alter the edge data to limit repeats of unnecessary edges (e.g., multiple edges positioned closely in parallel), which may have been captured as a result of data-acquisition noise during the operating of vehicle sensors…”).
Silver fails to specifically disclose the down sampling is used with a down sampling factor of 2.
However, Hansson, in the same field of endeavor teaches the down sampling is used with a down sampling factor of 2 (See at least page 9 of Hansson – “ As soon as less reliable radar detections have been discarded, it may be decided to use only the positions of the reliable detections… Dropping information … reduces the size of the radar data by a factor of two…which further keeps down the data payload…”). Thus, Silver discloses a system for a vehicle that obtains boundary data on a road in which a vehicle is travelling and manipulates the data to filter noise and repeating data to estimate boundaries ahead of the vehicle on the road, while Hansson teaches a system for aligning radar detection data that reduces radar data by a factor of two.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method, non-transitory computer-readable medium, and apparatus as disclosed in Silver to include the feature of the down sampling being used with a down sampling factor of 2 as taught by Hansson, with a reasonable expectation of success, in order to keep down the data payload as specified in at least page 9 of Hansson.
For claim 9, Silver discloses further comprising:
determining that an amount of data points of the second plurality of data points is larger than a threshold value (See at least Col. 17 lines 18-30 of Silver – “…the modifications executed by the computing system may alter the edge data to limit repeats of unnecessary edges (e.g., multiple edges positioned closely in parallel… as a result of data-acquisition noise during the operating of vehicle sensors…”); and
down sampling the second plurality of data points to obtain a third plurality of data points (See at least Col. 17 lines 18-30 of Silver – “… one example implementing involving executing modification upon a set or subset of edge data… the modifications executed by the computing system may alter the edge data to limit repeats of unnecessary edges (e.g., multiple edges positioned closely in parallel), which may have been captured as a result of data-acquisition noise during the operating of vehicle sensors…”).
For claim 10, Silver discloses further comprising:
determining that a maximum number of filter iterations is not reached (See at least Col. 20 lines 51-63 of Silver – “… The computing system may execute the smoothness check process in an iterative manner, which may involve constantly analyzing the boundary data … may use threshold determinations to filter boundary data to reflect boundaries that may actually exist in the vehicle's local environment...”); and
low pass filtering the second plurality of data points (See at least Col. 20 lines 51-63 of Silver – “… The computing system … may use threshold determinations to filter boundary data to reflect boundaries that may actually exist in the vehicle's local environment...”).
Claims 6-8 are rejected under 35 U.S.C. 103 as being unpatentable over Silver in view of Cherniak et al. US 20210173070 A1 (“Cherniak”).
For claim 6, Silver fails to specifically disclose further comprising applying a linear high pass filter on at least the first plurality of data points to generate a plurality of linearly high filtered data points.
However, Cherniak, in the same field of endeavor teaches further comprising applying a linear high pass filter on at least the first plurality of data points to generate a plurality of linearly high filtered data points (See at least [0034]-[0036] of Cherniak – “… modulator 540 addresses … nonlinearity issues using predistortion applied at the high-pass injection point to linearize the DCO … A pre-emphasis filter 652 acts as a high-pass filter on the adjusted FCW signal to compensate for the low-pass transfer function of the PLL 330…”). Thus, Silver discloses a system for a vehicle that obtains boundary data on a road in which a vehicle is travelling and manipulates the data to filter noise and repeating data to estimate boundaries ahead of the vehicle on the road, while Cherniak teaches a radar system that detects a target object and uses a linear high-pass filter on received signal values to linearize the signals.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method, non-transitory computer-readable medium, and apparatus as disclosed in Silver to include the feature of applying a linear high pass filter on at least the first plurality of data points to generate a plurality of linearly high filtered data points as taught by Cherniak, with a reasonable expectation of success, in order to compensate for the low-pass transfer function as specified in at least [0036] of Cherniak.
For claim 7, Silver fails to specifically disclose further comprising determining a localization of at least one object associated with the deviation between the at least one point of the first plurality of data points and the road layout based on the plurality of linearly high filtered data points.
However, Cherniak, in the same field of endeavor teaches further comprising determining a localization of at least one object (See at least [0020] of Cherniak – “… radar system 200 that utilizes a frequency hopping radar signal to detect objects…”) associated with the deviation between the at least one point of the first plurality of data points and the road layout based on the plurality of linearly high filtered data points (See at least [0027]-[0028] of Cherniak – “… The radar signal modulator 340 utilizes two-point injection … a high-pass injection signal… the low-pass injection signal and the high-pass injection signal together correspond to the bandwidth compensated signal … gain estimation circuitry 372 determines (e.g., using a least mean square (LMS) algorithm) a mismatch between the transfer function of the high-pass path and the transfer function of the low-pass path based on a sensed error…”). Thus, Silver discloses a system for a vehicle that obtains boundary data on a road in which a vehicle is travelling and manipulates the data to filter noise and repeating data to estimate boundaries ahead of the vehicle on the road, while Cherniak teaches a radar system that detects a target object, uses a linear high-pass filter on received signal values to linearize the signals, and determines a mismatch between sensed values using a high-pass filter and low-pass filter.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method, non-transitory computer-readable medium, and apparatus as disclosed in Silver to include the feature of determining a localization of at least one object associated with the deviation between the at least one point of the first plurality of data points and the road layout based on the plurality of linearly high filtered data points as taught by Cherniak, with a reasonable expectation of success, in order to compensate for the low-pass transfer function as specified in at least [0036] of Cherniak.
For claim 8, Silver fails to specifically disclose wherein determining the localization of the at least one object includes determining the localization of the at least one object based on a frequency distribution within the plurality of linearly high filtered data points.
However, Cherniak, in the same field of endeavor teaches wherein determining the localization of the at least one object includes determining the localization of the at least one object (See at least [0020] of Cherniak – “… radar system 200 that utilizes a frequency hopping radar signal to detect objects…”) based on a frequency distribution within the plurality of linearly high filtered data points (See at least [0028] of Cherniak – “… high-pass injection circuitry … combines the modulation signal … with the sequence of frequency offsets … to generate a frequency hopping modulation signal… the radar signal modulator 340 generates a frequency hopping radar signal…”). Thus, Silver discloses a system for a vehicle that obtains boundary data on a road in which a vehicle is travelling and manipulates the data to filter noise and repeating data to estimate boundaries ahead of the vehicle on the road, while Cherniak teaches a radar system that detects a target object, uses a linear high-pass filter on received signal values to linearize the signals, and determines a frequency distribution for the high filtered signals.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method, non-transitory computer-readable medium, and apparatus as disclosed in Silver to include the feature of determining the localization of the at least one object based on a frequency distribution within the plurality of linearly high filtered data points as taught by Cherniak, with a reasonable expectation of success, in order to compensate for the low-pass transfer function as specified in at least [0036] of Cherniak.
Conclusion
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/M.J.H./Examiner, Art Unit 3668
/Fadey S. Jabr/Supervisory Patent Examiner, Art Unit 3668